The Enterprise Technology Services organization partners with every part of the American Express business to power the company’s growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company’s technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.
The Sr. AI Engineer II leads the development of advanced AI/machine learning frameworks and innovative natural language processing models, translating complex business needs into scalable models, optimizing Big Data pipelines, ensuring compliance, and foster growth of individuals on the team.
- Supervises and mentors AI Engineers and cross-functional team of colleagues in specific tasks or projects, fostering their professional growth and ensuring adherence to best practices
- Ensures seamless integration of AI models into production systems, collaborating closely with cross-functional teams to facilitate smooth integration and ensure alignment and functionality
- Monitors and ensures compliance with model governance, security, and compliance standards, continuously monitoring models to ensure adherence to standards and proactively addressing issues
- Provides guidance and support to junior AI engineers, fostering professional growth and development within the team
- Drives the design and development of sophisticated AI/machine learning frameworks for large-scale data processing, focusing on prompt engineering and generative AI technologies
- Directs innovative approaches to apply machine learning algorithms for prompt engineering and natural language processing, solving complex problems and improving model performance
- Captures complex business requirements and translates them into sophisticated AI/machine learning-driven solutions, gathering and interpreting intricate business needs to develop advanced models and solutions
- Enhances and automates critical business processes by building and optimizing advanced Big Data pipelines and AI-based systems
- Leads implementation of new natural language processing models to classify and analyze complex business-related text data, ensuring accurate classification and insightful analysis
- Establishes and sustains comprehensive machine leanring operations pipelines that support scalable deployment, monitoring, and maintenance of AI models
- Leads design and evolution of complex, distributed AI systems, integrating multiple models, LLMs, and data services into cohesive platforms
- Drives development of advanced AI capabilities including multi-stage retrieval pipelines, autonomous workflows, orchestration frameworks, and system-level evaluation
- Establishes and enforces standards for AI reliability, safety, explainability, observability, and regulatory compliance across projects
- Collaborates and co-creates effectively with teams in product and the business to align technology initiatives with business objectives
- Manages complex tasks, requiring an in-depth evaluation of variable factors of moderate to substantial complexity
- Impacts multiple projects across multiple teams, influencing technical areas within the function
- Makes critical decisions that directly impact project success and operational efficiency
Education and Knowledge
- Bachelor's degree in Computer Science, Machine Learning, Data Science, and/or comparable experience; advanced degree preferred
- Knowledge of Python and data processing technologies such as Big Data (Hadoop, Spark)
- Knowledge of natural language processing techniques like fuzzy wuzzy and models such as BERT, Transformer models, and their real-world applications
- Deep expertise in machine learning, including tradeoffs in model selection, evaluation, and optimization
- Expert-level understanding of modern AI architectures, including LLM systems, agentic workflows, retrieval strategies, and scalable orchestration patterns
Work Experience
- Experience in software development with a focus on machine learning, generative AI, Big Data, and prompt engineering
- Experience in working with large language models (LLMs), especially GPT-3.5/4 or similar AI models
- Experience in languages such as Python, R, Java, or C++
- Experience in deploying AI models and pipelines using machine leanring operations tools
- Experience in machine learning algorithms and experience applying them to real-world problems
- Experience in continuous integration/continuous deployment pipelines and containerized deployments
- Experience in building and maintaining data pipelines and extract, transform, and load processes
- Extensive experience architecting and deploying large-scale AI systems in production environments
- Experience leading development of distributed AI platforms, real-time inference systems, and cloud-native AI services
- Advanced expertise in a technical domain, and moderate expertise across several different domains
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.